565 machine-learning "https:" "https:" "https:" "https:" "https:" "Bournemouth University" positions at University of Sheffield
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to develop cutting-edge imaging and analytical tools to answer fundamental biological questions about how tissues and tumours respond to mechanical stresses. Lab website: https://www.helenmatthewslab.org
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link for information on how to apply: https://www.sheffield.ac.uk/cbe/postgraduate/phd/how-apply. Please include the name of your proposed supervisor and the title of the PhD project within your
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Overview You will be part of a team that delivers a high quality, inclusive and accessible learning experience for all students. You will support students, actively seeking out and responding
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to the Faculty, University and Sheffield Teaching Hospital's policies and procedures. Ensure all work is embedded in the University's Strategic Plan. (http://www.sheffield.ac.uk/ourplan/) . Act in accordance with
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Delivery Staff Our website https://sheffield.ac.uk/ctru For informal enquiries about this job contact Prof Matt Hammond, Director of the Sheffield Clinical Trials Research Unit: on matthew.hammond
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Feedback control of tokamak plasmas via deep learning policies with robustness guarantees (S3.5-ELE-Drummond) School of Electrical and Electronic Engineering PhD Research Project Competition Funded
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on the research conducted as part of an NIHR funded grant which comes to an end in July 2026 “Improving access to cervical screening for physically Disabled people” (https://www.dev.fundingawards.nihr.ac.uk/award
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the ability to learn new software. Essential Application/interview The ability to handle, manipulate and interpret large data sets, and to work to the highest degree of accuracy with attention to detail
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with an appreciation of longer-term implications. Essential Application/interview Willingness to update and acquire new skills and knowledge in line with advances in the relevant subject area, including
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webpages for further information: https://www.sheffield.ac.uk/postgraduate/phd/scholarships Loans are available to eligible home fee-paying doctoral students studying postgraduate research courses: https